1. Technical Field
The present disclosure relates to pulmonary emboli detection and, more specifically, to pulmonary emboli detection with dynamic configuration based on blood contrast level.
2. Discussion of Related Art
A pulmonary embolism (PE) is a blockage, for example a clot, within the arteries that carry blood from the heart to the lungs including the pulmonary artery or one of its branches. Pulmonary emboli can be deadly but may be treated if properly detected. The presence of PEs may be detected with the use of pulmonary angiography. Pulmonary angiography may involve catheterisation of the right atrium of the heart and injection of radiocontrast into the right heart.
Less invasive approaches for the detection of pulmonary emboli have been developed. For example, CT imaging may be used to provide CT pulmonary angiography (CTPA) without the need for injecting radiocontrast directly into the heart. In these approaches, a computer tomography (CT) scanner is used to image the vessel tree and pulmonary arteries of the lungs.
Detection of PEs within the CT images may be performed either manually or automatically. In manual PE detection, a trained medical practitioner, for example a radiologist, manually reviews the CT data to locate evidence of a PE. This practice may be particularly time consuming and tedious as modern CT images contain a vast amount of data.
Moreover, manual reading of the CT image data may be further complicated by various image abnormalities that may look like a PE and may thus lead to a false positive. Examples of such image abnormalities include respiratory motion artifacts, flow-related artifacts, streak artifacts, partial volume artifacts, stair step artifacts, lymph nodes, and vascular bifurcation, among many others.
Upon diagnosis of a PE, an extended course of anti-clotting medications are administered. While treatment may be life-saving to a patient suffering from an actual PE, these medications may lead to bleeding so it is important that misdiagnosis such as false-positive identifications be minimized.
In automatic PE detection, the CT data is analyzed by a computer to detect either a PE or to select regions of suspicion that may be brought to the attention of the radiologist. The radiologist may then pay particular attention to the selected regions of suspicion. Accordingly, automatic PE detection may reduce the amount of time necessary to review CT data for evidence of a PE and may increase accuracy of detection by bringing regions of suspicion, which may have otherwise gone unnoticed, to the attention of the radiologist.
Radio-opaque contrast plays an important role in CTPA. In acquiring CTPA images, the bolus tracking technique is often used to clearly visualize vessels. According to this technique, a bolus of radio-opaque contrast is injected into the patient using a peripheral intravenous cannula. The volume of contrast is then tracked by the CT scanner. CT images are then acquired at a rate fast enough to capture the progress of the contrast moving through the blood vessels.
Image quality may be influenced by the degree to which the radiocontrast mixes with the blood once administered. Several factors such as body weight and injection duration may affect the extent to which proper mixing occurs. While such factors may be controlled for, to some degree, other factors such as the flow rate of the blood can also affect the extent to which proper mixing occurs, and factors such as these may be difficult to control for. Improper mixing of the radiocontrast in the blood may create mixing artifacts in the CTPA images that may result in a suboptimal CTPA study due to non-homogeneous enhancement of blood, as observed by HU values.
Suboptimal CTPA studies may then lead to increased occurrences of false positive PE detection and then perhaps to the needless administration of treatments with serious side effects. On the other hand, suboptimal CTPA studies may lead to increased occurrences of false negatives where patients may not be given potentially life-saving treatments.